Journal of Magnetic Resonance Imaging

Introduction: This study aimed to characterize the neurochemical profile of Alzheimer s disease (AD) continuum stages using proton magnetic resonance spectroscopy (1H-MRS) data for brain metabolites and macromolecules. We used Orthogonal Projection to Latent Structures Discriminant Analysis (OPLS-DA) to classify diagnostic groups and assess feature importance. Methods: Our dataset consisted of 7 T short-echo time 1H-MRS spectra of the posterior cingulate cortex/precuneus of individuals diagnosed with AD (n = 27) or Mild Cognitive Impairment (MCI, n = 27) and Healthy Controls (HC, n = 31). Classification used 100-round Monte Carlo cross-validation based on metabolite concentrations and macromolecular peak intensities. Variable importance in projection (VIP) was assessed across classification models to identify the most relevant neurochemical features. The resulting metabolite rankings were compared with previous literature to evaluate their biological plausibility. Results: Classification was strongest for AD versus HC (AUC=0.88) and lower for comparisons involving MCI. Metabolites contributing most strongly to classification included myo-inositol, ascorbate, and choline-containing compounds, consistent with previous studies on AD-related neurochemical alterations. In addition, specific macromolecular components were identified as relevant features, suggesting a potential contribution of MM signals to the characterization of AD-related neurochemistry. Discussion: These findings support the use of short-echo-time 1H-MRS as a complementary tool for characterizing neurochemical changes in the AD continuum, with potential applications in disease characterization and monitoring, warranting validation in larger cohorts.

Purpose: Proton density (PD) and macromolecular proton fraction (MPF) are fundamental MR parameters characterizing water and macromolecular content in tissues. Both parameters can be mapped using a time-efficient MRI protocol, though PD maps require additional corrections for the reception profile (RP) non-uniformity and global scaling. Existing PD mapping methods suffer from uncertainties related to PD normalization to reference tissue. This study aimed to develop a data-driven RP correction method for PD mapping based on MPF as an internal scale. Theory and Methods: One-parameter model linking PD and MPF was derived under assumption of proportionality between total macromolecular volume and proton concentration. This model with a uniform parameter value across brain tissues generates a surrogate PD map, which is used to estimate RP from an uncorrected PD map. The proposed algorithm was tested against a common PD mapping method utilizing bias-field correction and normalization to cerebrospinal fluid. Brain MRI data were acquired at 3T from seven healthy individuals. The protocol included 3D multi-echo T1-, PD-, and magnetization-transfer-weighted gradient-echo sequences. Parametric maps were reconstructed using the single-point MPF mapping algorithm with data-driven B1 correction. Results: MPF-based and bias-field corrections yielded similar PD measurements in white and gray matter with no significant bias and remarkably small variability (coefficients of variation <0.6%). Conclusions: MPF-based RP correction enables computationally simple and robust quantitative PD mapping at no additional cost if MPF maps are available. The main advantage of the proposed method is automatic elimination of global scaling that obviates the need for PD normalization.

Purpose: To evaluate whether visually assessed high-quality prostate MRI, as defined by the Prostate Imaging Quality (PI-QUAL) scoring system, is sufficient to ensure consistent AI model performance, or whether hidden acquisition-related technical effects introduce variability that cannot be detected through visual inspection. Methods: This retrospective study included 568 bpMRI scans from seven institutions, classified using PI-QUAL v2 into high-quality (scores 2-3) and low-quality (score 1) groups. Quantitative image quality features were extracted using MRQy from T2w and ADC sequences. Three experiments were conducted on high-quality scans: (1) unsupervised clustering to identify hidden technical batch effects; (2) V-Net models (M) for prostate capsule segmentation on T2w using single-cluster and balanced multi-cluster training strategies; and (3) VoxelMorph-based deformable registration (M2) to align ADC maps to T2w images. Performance metrics included DSC, precision, recall, volume ratio, HD95, ASSD, and TRE. Kruskal-Wallis tests assessed cross-cluster variability, Two One-Sided Tests (TOST) evaluated performance equivalence, and bootstrap resampling quantified training efficiency. Results: Clustering identified four clusters among 277 high-quality bpMRI scans. Single-cluster models showed variable performance (DSC=0.41-0.85) with significant batch effects (p<0.001), even with 140 training samples. The balanced multi-cluster model (n=60) eliminated batch effects (p=0.075), achieved equivalent performance (p<0.001), and demonstrated 2.23-fold greater training efficiency despite using 2.3-fold fewer samples. Registration performance also varied significantly across clusters (TRE=0.86-5.47 mm, p<0.001). Conclusion: Acquisition-related batch effects significantly impact AI generalizability in prostate MRI, even among high-quality scans. Quantitative clustering enables detection of technical variations and supports diversity-aware training strategies that achieve equivalent performance with 2.3-fold fewer samples while eliminating batch effects.

Purpose: Posterior pharyngeal wall (PPW) thickening is a common structural manifestation of treatment-related internal lymphedema in patients with head and neck cancer and can be evaluated using lateral videofluoroscopic images acquired during modified barium swallow (MBS) studies. However, no standardized method currently exists for quantitative measurement. Methods: This two-phase methodological study first conducted a scoping review to characterize existing approaches to PPW thickness measurement and identify the principal factors contributing to variation in PPW thickness measurement. Eight studies were identified with variation observed across these measurement factors. An empirical reliability study was then performed using 107 MBS studies from 93 Head and Neck Cancer patients. Two independent raters annotated 10 anatomical landmarks on pre-swallow and post-swallow resting frames, and a computer-assisted algorithm quantitatively generated seven candidate PPW thickness measurements based on different vertebral reference points and measurement directions. Reliability was assessed intraclass correlation coefficients (ICCs). Results: Inter-rater reliability was highest for the measurement originating from the midpoint of C3 and extending perpendicular to the anterior C3 surface (ICC, 0.78; 95% CI, 0.72-0.83). Among the normalization references, C2-C4 vertebral length demonstrated greater reliability than C3 vertebral length, with an ICC of 0.88 (95% CI, 0.85-0.91). No significant differences were observed between pre-swallow and post-swallow PPW thickness measurements across the evaluated approaches. Conclusions: These findings provide a methodological foundation for more standardized and reliable quantification of PPW thickness, with potential to expand the role of MBS from the functional evaluation of swallowing to include quantitative characterization of pharyngeal structural abnormalities.

Background: Ultra-low field (ULF) magnetic resonance imaging (MRI) offers accessible point-of-care neuroimaging, yet its capability to support multivariate network analyses remains understudied. Methods: We systematically evaluated the feasibility and reliability of Morphometric Similarity Networks (MSN) and Morphometric Inverse Divergence (MIND) networks derived from paired high-field (HF, 3T/1.5T) and ULF (64mT) scans in a primary cohort(N=23) and an independent replication cohort (N=19). We tested the impact of super-resolution processing, cortical parcellation granularity (Desikan-Killiany vs. Destrieux), and mesh resolution (fsnative vs. fsaverage5) on edge-level cross-scanner agreement (Lin's concordance correlation coefficient, CCC) and subject-level identifiability. Results: MIND networks demonstrated higher edge-level HF-ULF agreement (mean CCC = 0.95) and ULF reproducibility (mean CCC = 0.98) compared to MSNs (mean CCC = 0.86-0.87 and 0.91-0.94, respectively). In contrast, MSNs yielded higher subject-level differential identifiability across field strengths due to a broader distinction between within- and between-subject similarity. Reconstructing MIND networks on native high-resolution meshes (fsnative) maximised cross-scanner agreement, whereas coarser meshes and finer cortical parcellations enhanced individual network identifiability. Conclusions: Structural similarity networks can be reliably constructed from ULF MRI data. Optimal analytic choices depend on study objectives: MIND on native meshes maximises cross-scanner stability, whereas MSNs excel at preserving individual uniqueness, paving the way for globally scalable connectomic research.

Background: Cervical spinal cord (CSC) compression and myelopathy are frequent, severe complications in mucopolysaccharidosis (MPS) types I and VI. Early detection is critical to prevent irreversible neurological deficits and preserve quality of life. This prospective study aimed to identify quantitative neuroimaging biomarkers of structural CSC damage and myelopathy in MPS I and VI. Methods: Structural and diffusion magnetic resonance imaging (MRI) of the CSC was analyzed in 17 MPS I patients, 3 MPS VI patients (19{+/-}7 years), and 19 case-matched healthy controls (20{+/-}7 years). CSC macrostructure (cross-sectional area, diameters) and microstructure (fractional anisotropy [FA], radial [RD], mean, axial diffusivities) were evaluated within and beyond the maximal compression areas. Results: MPS patients demonstrated reduced CSC cross-sectional area and anterior-posterior diameter at upper cervical levels, alongside widespread microstructural alterations (lower FA, higher RD) throughout the CSC versus controls (pFDR<0.05). Restricted foramen magnum space was associated with microstructural damage at lower cervical levels without overt macrostructural compression. Morphological and microstructural metrics were sensitive to CSC compression and myelopathy severity (pFDR<0.05). Lower CSC integrity correlated with more advanced growth retardation (p<0.001). Among patients receiving hematopoietic stem cell transplantation, earlier treatment correlated with preserved upper CSC morphology (p<0.05). Distinct neuroimaging phenotypes were observed across MPS genotypes (pFDR<0.05). Conclusions: CSC MRI provides candidate neuroimaging biomarkers for early detection and characterization of myelopathy in MPS I and VI. Structural damage extends beyond primary maximal compression areas, highlighting these markers for clinical monitoring and future therapeutic trials.

Patients with implantable cardioverter-defibrillators (ICDs) often are excluded from receiving CMR scans at 3.0T due to ICD-induced image artifacts. This work aims to transfer sequence protocols established for CMR imaging in the presence of ICDs at 1.5T to a first human application at 3.0T. All measurements were performed on a clinical 3T MRI scanner. Phantom measurements were used to establish and optimize wideband PSIR LGE imaging at 3.0T. Volunteer measurements with externally placed ICDs were used for optimization of CINE imaging and wideband PSIR imaging. Thirdly, patients with implanted ICD were examined with the optimized protocols. Human measurements showed that SA stacks obtained with spoiled GRE after contrast agent showed a markedly lower artifact burden than the conventional approach. For scar imaging, a wideband PSIR with a bandwidth of 3kHz and a frequency offset of +750Hz allowed a sufficient suppression of relevant artifacts in the majority of scans. No strong correlation between the image quality and the distance between the cardiac silhouette and the device was detected. The presented work shows the feasibility of clinical cardiac MRI at 3.0T including GRE-CINE and wideband PSIR-LGE for patients with ICDs.

Objectives To evaluate discrepancies between radiologists and referring physicians in the interpretation of diagnostic probabilities conveyed by common Japanese expressions used in radiology reports. Materials and Methods Fifteen expressions commonly used to convey diagnostic probabilities in radiology reports were selected by five attending radiologists. An anonymous online survey was distributed to 26 radiologists and 33 referring physicians at a single institution. Participants assigned a diagnostic probability (from 0% to 100% in 10% increments) to each expression. Differences in median probabilities between radiologists and referring physicians were analyzed using the Mann-Whitney U test. Variability in interpretation was assessed using interquartile range (IQR), with IQR [&ge;] 30% defined as substantial variability. Results All radiologists (26/26) and 97% of referring physicians (32/33) completed the survey. Seven of the 15 expressions showed statistically significant differences in interpretation between radiologists and referring physicians: "c/w" (80% vs. 60%; p = 0.031), the Japanese equivalents of "present" (100% vs. 100%; p = 0.024), "suspect of" (80% vs. 70%; p = 0.007), "possibly" (50% vs. 70%; p < 0.001), "unlikely" (10% vs. 10%; p = 0.022), "cannot be ruled out" (25% vs. 40%; p < 0.001), and "not inconsistent with" (80% vs. 90%; p = 0.008). Substantial variability in interpretation (IQR [&ge;] 30%) was observed for four expressions: "cannot be ruled out" (IQR, 10%-40%), "s/o" (IQR, 60%-90%), "c/w" (IQR, 50%-90%), and "not inconsistent with" (IQR, 70%-100%). Conclusion This study revealed that nearly half of the Japanese expressions commonly used to convey diagnostic probabilities were interpreted differently by radiologists and referring physicians. These discrepancies highlight the need for a standardized lexicon to improve clarity and consistency in radiology reporting.

Background: Quantitative susceptibility mapping (QSM) exhibits phase cancellation between paramagnetic (e.g. iron) and diamagnetic (e.g. myelin/protein) sources, obscuring microstructural lesion heterogeneity in multiple sclerosis (MS). We evaluated whether biophysical {chi}-separation identifies clinically meaningful lesion phenotypes and whether reduced echo sampling preserves microstructural sensitivity. Methods: In this cross-sectional study of 183 people with multiple sclerosis (PwMS), we analyzed 3327 quality-controlled white matter lesions using 3T MRI with a five-echo gradient-recalled echo sequence (GRE5) and a subsampled two-echo dataset (GRE2). A hybrid framework combining unsupervised clustering on whole-lesion paramagnetic ({chi}para) and diamagnetic ({chi}dia) features with rule-based compartmental edge-core gradient assignment resolved MS lesion phenotypes. Intralesional microstructural properties were evaluated using linear mixed-effects models. Multivariable linear regressions assessed associations with physical disability (Expanded Disability Status Scale, EDSS; n = 158), cognitive processing speed (Symbol Digit Modalities Test, SDMT; n = 79), and disease duration (DD; n = 161), with sensitivity models adjusting for total lesion volume, count, or DD. Results: The framework identified four reproducible lesion phenotypes (Adjusted Rand Index = 0.924): Type 1 (22.7%; preserved {chi}dia), Type 2 (32.9%; high {chi}para without positive edge-core gradient), Type 3 (35.8%; attenuated {chi}dia), and Type 4 (8.6%; high {chi}para with a positive edge-core paramagnetic gradient). Higher EDSS was selectively associated with more negative signed {chi}dia within Type 4 lesions (whole: {beta} = -0.37, q = 0.020; core: {beta} = -0.37, q = 0.006; edge: {beta} = -0.34, q = 0.030) and Type 2 edge ({beta} = -0.33, q = 0.044). Type 4 core associations remained robust across sensitivity models adjusting for total lesion volume ({beta} = -0.35, q = 0.004), total lesion count ({beta} = -0.37, q = 0.008), and DD ({beta} = -0.32, q = 0.033). Abbreviated GRE2 attenuated Type 4 compartmental associations to non-significance (all q greater than 0.05; core: {beta} = -0.20, q = 0.215). Conclusions: Quantitative {chi}-separation identified four internally stable susceptibility-defined MS lesion phenotypes, revealing disability-associated tissue heterogeneity beyond total lesion burden. Higher EDSS was associated with more negative diamagnetic measures within Type 4 cores after adjustment for lesion burden, pointing toward complex intralesional non-myelin tissue remodeling or reactive astrogliosis. Two-echo subsampling may influence compartment-specific clinical associations. By uncoupling susceptibility sources, {chi}-separation provides a quantitative framework for characterizing disability-associated lesion heterogeneity.

Objectives: To determine how strongly clinical referral text, rather than image content, drives the decisions of multimodal large language models (LLMs) differentiating glioma from brain abscess on MRI. Materials and methods: This retrospective single-center study included 60 contrast-enhanced T1-weighted brain MRI examinations (30 gliomas, 30 abscesses; reference-standard diagnosis). One axial slice per case was paired with five referral texts (explicitly inflammatory to explicitly tumor-suggestive) under three prompt instructions and submitted 20 times each to GPT-4o, Claude Sonnet 5, Gemini 3.5 Flash, and Qwen 3.6 (72,000 answers). The primary outcome was the text-driven span (difference in tumor-call frequency between explicit inflammatory and explicit tumor text). Two blinded radiologists classified the images without text; sensitivity, specificity, and accuracy were compared descriptively. Results: Patients (29 women) had a mean age of 55.8 +/- 16.4 years. With neutral text, models answered tumor in 45-67% of queries (specificity, 0.38-0.78), versus 52% and 60% for radiologists (specificity, 0.77 and 0.63). The text-driven span was 0.79-1.00 (p < 0.001 for all models), whereas confirmed gliomas and abscesses differed by only 0.01-0.10 in three models and 0.25 in Gemini 3.5 Flash. Subtle wording produced at least 83% of the span in three models. An instruction to ignore the text reduced the span to 0.48-0.70 in three models and to 0.04 in Gemini 3.5 Flash, partly through reversion to a tumor default. Model accuracy was 0.52-0.73 versus 0.78 and 0.73 for radiologists. Conclusion: Multimodal LLMs deferred to referral text over imaging evidence in differentiating glioma from brain abscess, and prompt instructions did not reliably correct this.

Background: Mitochondrial dysfunction is a hallmark of ageing and is implicated in the pathogenesis of sarcopenia. Genetically confirmed mitochondrial disease provides a biologically definitive model of impaired oxidative phosphorylation against which novel functional assessments can be validated. We investigated whether a brief, submaximal, non-ischaemic intermittent isometric handgrip exercise protocol combined with Near Infra-Red Spectroscopy (NIRS) could detect distinct muscle oxygenation signatures in mitochondrial disease and sarcopenia. Methods: Adults with genetically confirmed mitochondrial disease (n=10, 7 female) and group-matched controls (n=19, 11 female), underwent assessment of maximal grip force, handgrip relaxation kinetics and a 3-minute intermittent submaximal isometric handgrip test (40% maximal voluntary contraction, 1Hz contraction/relaxation) with continuous force recording at 2000Hz and simultaneous NIRS. Findings were compared with 23 community-dwelling older adults from the Muscle Ageing and Sarcopenia Study (MASS) Lifecourse cohort (n=23, 13 female) including seven with probable or confirmed sarcopenia according to European Working Group on Sarcopenia in Older People (EWGSOP2) criteria. Results: Participants with mitochondrial disease demonstrated an attenuated reduction in tissue saturation index (TSI) during exercise compared with controls (TSI % {middle dot} s150-180s: -59.9 {+/-} 94.5 vs -175.1 {+/-} 128.4; p=0.02). Total haemoglobin (THb) responses did not differ between groups (p=0.10). In contrast, participants with probable or confirmed sarcopenia showed exaggerated reduction in TSI compared with non-sarcopenic participants (TSI % {middle dot} s150-180s: -256.5 {+/-} 146.0 vs -121.2 {+/-} 95.2; p=0.05), while THb responses remained similar. The association between sarcopenia and TSI differed by sex (interaction coefficient -240, p=0.016), with greater TSI reductions observed in males with sarcopenia. Differences in TSI between mitochondrial disease and control groups were independent of age and sex. No statistically significant associations were observed between THb responses and age, sex or force production. Conclusions: A brief, non-ischaemic handgrip exercise protocol combined with NIRS identified divergent muscle oxygenation responses in mitochondrial disease and sarcopenia. The attenuated TSI response observed in genetically confirmed mitochondrial disease is consistent with impaired oxygen utilisation secondary to defective oxidative phosphorylation, whereas the exaggerated TSI reduction observed in sarcopenia suggests a distinct physiological mechanism, potentially involving impaired oxygen delivery, reduced muscle efficiency, or both. This portable and non-invasive approach has significant potential as a physiological biomarker for mechanistic studies and clinical trials in ageing and neuromuscular disease. More broadly, our findings demonstrate how biologically defined rare diseases can provide a powerful framework for interpreting mechanisms in common heterogeneous age-related conditions.

Background: Peripheral inflammation has been implicated in the pathophysiology of Parkinson's disease (PD), but its relationship with autonomic dysfunction remains unclear. Objectives: To explore the association between peripheral inflammation, assessed by the neutrophil-to-lymphocyte ratio (NLR), and autonomic function in patients with PD. Methods: We retrospectively analyzed 97 patients with PD who underwent 123I-metaiodobenzylguanidine (MIBG) cardiac scintigraphy and differential blood cell counts. Associations of NLR with early and delayed heart-to-mediastinum (H/M) ratios, washout ratio, and the coefficient of variation of R-R intervals (CVRR) were assessed using Spearman's rank correlation and multivariable linear regression adjusted for age, sex, and disease duration. Results: No significant univariable correlations were observed between NLR and the autonomic measures. In multivariable analysis, higher NLR was associated with a lower early H/M ratio (B = -0.802, 95% CI -1.598 to -0.005, P = 0.049), whereas no significant associations were observed with the delayed H/M ratio, washout ratio, or CVRR. Sensitivity analyses showed a generally consistent direction of association, although the effect estimate was attenuated after exclusion of two influential observations and statistical significance was not consistently retained. Conclusions: Higher NLR was associated with lower early cardiac MIBG uptake after adjustment for age, sex, and disease duration in patients with PD. This exploratory finding raises the possibility of an association between systemic inflammation and sympathetic dysfunction in PD and requires confirmation in larger prospective studies.

Introduction: Neuroinflammation is a known pathophysiologic mechanism in multiple sclerosis and a proposed mechanism in fibromyalgia and myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). Positron Emission Tomography (PET) imaging of the translocator protein (TSPO) has been widely used to measure neuroinflammation, though second-generation ligands are highly sensitive to a single nucleotide polymorphism, rs6971, resulting in high, mixed, and low affinity binders. It is unknown whether this polymorphism is associated with neuroinflammatory disorders. Materials and Methods: Eighty-six total participant genotypes for TSPO binding affinity were identified through Sanger sequencing (30 fibromyalgia, 21 ME/CFS, 11 multiple sclerosis, and 24 healthy controls). Associations between patient group and genotype were assessed with Fishers Exact test. Associations between genotype and symptom severity from self-report questionnaires were assessed with Kruskal-Wallis tests. Results: In the present study individuals with fibromyalgia, (ME/CFS), or multiple sclerosis were more likely to have a mixed- or low-affinity genotypes compared to healthy controls. Presence of the low or mixed genotypes were also associated with greater self-reported fatigue severity and depressive symptoms. Discussion: These findings should be confirmed in larger samples but suggest functional consequences of rs6971 polymorphism that may be related to the pathophysiology of pain and fatigue illnesses.

Computed tomography (CT) interpretation requires recognition of the anatomical level of each slice. Classification may facilitate preprocessing and AI-assisted fracture diagnosis. We developed deep learning models to classify craniofacial CT slices into six anatomical categories. A total of 11,769 images were collected from a multicenter database involving 10 Japanese university hospitals and the public Head-Neck-Radiomics-HN1 dataset. Patients were divided into training (70%) and evaluation (30%) sets. Five CNN architectures were trained from scratch, and hard- and soft-voting ensembles were evaluated. Individual-model accuracy ranged from 94.72% to 96.09%; the hard-voting ensemble achieved 96.46% accuracy (Cohen's k = 0.954). Although performance differed among individual models (Cochran's Q = 99.29, p < 0.001), the ensemble did not significantly outperform EfficientNetV2B1 (McNemar's p = 0.163). Errors occurred mainly between adjacent anatomical regions. Deep learning can classify craniofacial CT slices accurately and may support automated dataset organization and AI-assisted fracture diagnosis. External validation is needed.

Importance: Blood biomarkers for Alzheimer disease(AD), Parkinson disease(PD), and amyotrophic lateral sclerosis(ALS) are typically developed as disease-specific single-analyte tests. Whether one shared plasma panel can support disease-selective classification remains unclear. Objective: To test whether the Olink Target 48 Neurodegeneration plasma panel, analyzed with disease-specific Elastic Net models, can discriminate AD, PD, and ALS in a heterogeneous neurological cohort. Design, Setting, and Participants: Single-center diagnostic cohort study at Keio University Hospital, Tokyo, Japan. After quality control and one consent withdrawal, 302 participants were analyzed(healthy controls n = 62; AD continuum n = 93; PD n = 39; ALS n = 27; other neurological disorders n = 81) and allocated by diagnosis-stratified sampling into a discovery training set(n = 211) and a locked hold-out test set(n = 91). Exposures: Plasma normalized protein expression from 42 assays retained after protein quality control. Plasma DOPA decarboxylase was excluded a priori from all classifiers because blood levels primarily reflect dopaminergic treatment exposure. Main Outcomes and Measures: Hold-out receiver operating characteristic area under the curve(AUC). Sensitivity and specificity at a training-set Youden threshold locked for Test. Results: Hold-out AUCs were 0.974(95% CI, 0.942-0.995) for AD, 0.926(0.820-1.000) for PD, and 0.995(0.980-1.000) for ALS. At locked Youden cutoffs, sensitivity was 0.929 (95% CI, 0.765-0.991) and specificity was 0.921 (95% CI, 0.824-0.974) for AD, 0.833 (95% CI, 0.516-0.979) and 0.975 (95% CI, 0.912-0.997) for PD, and 1.000 (95% CI, 0.631-1.000) and 0.940 (95% CI, 0.865-0.980) for ALS. Conclusions and Relevance: A single plasma neurodegeneration panel supported disease-selective classification of AD, PD, and ALS in internal validation. Multicenter external validation is needed before clinical application.

Background: Conventional performance metrics do not indicate whether artificial intelligence (AI)-platforms and radiologists are right or wrong on the same examinations, nor whether their non-agreement is more often beneficial or harmful. Objective: To develop, illustrate, and apply directional metrics quantifying non-agreement between radiologists and AI-platforms against a common reference standard, and to adapt a fragility-based framework for quantifying the statistical robustness of these metrics. Methods: We defined Positive Non-Agreement (PNA, AI-platform correct, radiologist incorrect), Negative Non-Agreement (NNA, radiologist correct, AI-platform incorrect), and Net Non-Agreement (NENA, their difference). Metrics were illustrated in three hypothetical scenarios of 1,000 examinations each and applied to three previously published AI-radiologist studies on pulmonary embolism and mammography. Bootstrap confidence intervals were calculated, and a reclassification fragility index (FI) quantified the minimum case reclassification needed to remove statistical support for NENA's direction. Results: In illustration, NENA was positive in two scenarios and negative in one. In the three published studies, NENA ranged from -4.18% to +10.74% and decreased consistently with increasing radiologist experience (junior residents, +6.27%; consultants, +1.45%), a gradient driven primarily by declining PNA with modest increase in NNA. The reclassification FI was defined for all three illustrative scenarios (range, 0.10%-1.70%) and for six of the seven comparisons from these studies (range, 0.34%-4.31%), but not for the weakest comparison, whose confidence interval for NENA included zero. Conclusions: PNA, NNA, and NENA provide a directional, case-level complement to conventional performance metrics for AI-radiologist non-agreement. The accompanying reclassification FI offers a statistically grounded, generalizable method for quantifying their robustness.

Background: Dopamine replacement reshapes subthalamic activity in Parkinson's disease, but whether this response reflects anatomically organized network reconfiguration remains unclear. Objectives: To determine whether levodopa preferentially reorganizes dorsal subthalamic spectral activity and cortico-subthalamic directionality. Methods: Twelve participants undergoing bilateral subthalamic deep brain stimulation contributed 30 contacts (14 dorsal, 16 ventral). Recordings obtained OFF and ON medication underwent spectral parameterization and multiband state-space analysis. Simultaneous electroencephalography in six participants enabled assessment of directional cortico-subthalamic coupling using the phase slope index. Results: Levodopa suppressed beta power more strongly dorsally than ventrally (-2.473 versus -0.120 dB; p=0.0438). Dorsal theta power increased, with a trend toward an increase after baseline normalization (p=0.07). Dorsal contacts exhibited greater theta-beta (+5.904 versus +1.610 dB; p=0.006) and gamma-beta (+2.516 versus +0.384 dB; p=0.0188) state-space shifts, principally driven by beta suppression. Gamma changes did not differ regionally. Concurrently, dorsal low-beta and beta interactions shifted toward cortical leading at selected electrodes, whereas ventral responses were less consistent. Conclusions: Levodopa produces a topographically organized subthalamic response, combining preferential dorsal beta suppression with altered cortico-subthalamic directionality. These findings position contact anatomy as a key consideration in characterizing dopaminergic network responses and motivate clinical validation of spatially informed multiband biomarkers for adaptive stimulation.

Introduction: Cognitive intraindividual variability (IIV), a measure of fluctuation in performance across time or tasks, is an emerging marker of cognitive decline. However, little is known about within-domain IIV in Latino adults. To address this gap, we examined memory IIV and hippocampal integrity in older Latino individuals. Methods: Sixty-seven participants from the Boston Latino Aging Study underwent cognitive testing and MRI. Linear regressions assessed whether memory IIV was associated with hippocampal volume and hippocampus-cingulum tract fractional anisotropy. Additional analyses evaluated associations using mean memory performance as the outcome. Results: Higher mean performance was associated with greater hippocampal volume (=0.24, p=.03), while memory IIV was not (=0.028, p=.84). Higher memory IIV was associated with lower fractional anisotropy in the hippocampus-cingulum tract (=-0.34, p<.01), while mean performance was not (=-0.07, p=.52). Discussion: Memory IIV may be more closely linked to hippocampal white matter, while mean memory performance may better reflect hippocampal volume.

Over 30% of patients with epilepsy are refractory to medication and may require surgical or neuromodulation-based intervention. Accurate localization of seizure-onset zones (SOZ) and assessment of treatment-associated brain responses remain major clinical challenges. Current workflows may involve invasive intracranial monitoring, prolonged hospitalization, adjustment of anti-seizure medications, and seizure capture to localize the SOZ, while opportunities for complementary intraoperative functional assessment remain limited. We used intraoperative functional ultrasound imaging (fUSI) to characterize interictal (i.e., non-seizure) cortical activity in nine patients with drug-resistant focal epilepsy and to assess treatment-associated brain responses following SOZ resection and responsive neurostimulation (RNS). fUSI signals were acquired directly from the exposed cortex during standard-of-care surgery. We developed six ultrafast power Doppler-based interictal activity markers (IaMs) to distinguish SOZ from peri-resection zone (PRZ) cortex and to quantify treatment-associated changes. The IaMs revealed distinct interictal hemodynamic dynamics between SOZ and PRZ cortex. Following SOZ resection, all six markers changed significantly within the surrounding PRZ. RNS also induced robust, stimulation paradigm-dependent modulation of cortical hemodynamic dynamics. Notably, RNS and surgical resection produced concordant directional changes across five of the six IaMs, despite representing fundamentally different therapeutic interventions. Together, these findings demonstrate the feasibility of intraoperative fUSI for characterizing and distinguishing interictal dynamics within SOZ and PRZ cortex and assessing treatment-associated cortical responses during human epilepsy surgery. Furthermore, fUSI could provide a complementary high-resolution functional imaging approach alongside established clinical methods for SOZ localization and intraoperative functional assessment.

Background and Objectives Transient ischemic attack (TIA) diagnosis is challenging because it relies mainly on clinical assessment and exclusion of common differential. Functional MRI (fMRI) may provide a diagnostic biomarker by detecting transient brain dysfunction not visible on conventional imaging. This pilot study aimed to characterize acute motor-task BOLD activation in patients with suspected DWI-negative TIA and compare functional patterns between confirmed TIA and alternative diagnoses. Secondary objectives were to assess longitudinal changes in activation and connectivity at 3 months. Methods In this prospective single-center study, adults presenting within 24 h of transient anterior-circulation neurological symptoms underwent conventional MRI and additional motor-task fMRI. Patients with acute DWI lesions were excluded. Final diagnosis was established after 3-month follow-up. Whole-brain analyses, individualized motor cortex region-of-interest (ROI) analyses, and generalized psychophysiological interaction (gPPI) connectivity analyses were performed during the acute phase and at 3 months. Results Eight patients were enrolled; six had complete longitudinal imaging data and were included in the final analyses. Final diagnoses were TIA (n=2), migraine aura (n=2), functional neurological disorder (n=1), and hypoglycemia (n=1). Whole-brain and ROI analyses showed reduced bilateral motor-related BOLD responses during the acute phase in both TIA patients and in the patient with hypoglycemia. In contrast, patients with migraine and functional neurological disorder exhibited less marked longitudinal changes. In TIA patients, motor cortex activation increased at 3 months, tending to normalize toward values observed in non-TIA participants. Connectivity analyses revealed heterogeneous patterns, but the 2 TIA patients demonstrated increased longitudinal connectivity between the motor cortex contralateral to symptoms and other sensorimotor regions, including supplementary motor, premotor, parietal, and postcentral cortices. Discussion These preliminary findings suggest that TIA may be associated with transient bilateral reductions in motor-network activity. Functional abnormalities appeared to improve over time, supporting the hypothesis of reversible network dysfunction. Although limited by the very small sample size, this study provides the first longitudinal assessment of emergency task-based fMRI in rigorously defined TIA and supports further investigation of acute functional MRI as a potential biomarker of transient cerebral dysfunction.